The present invention relates, in general, to fossil or other organic fuel boilers and, in particular, to a new and useful method of optimizing the scheduled timing of sootblowing in such boilers.
The combustion of fossil fuels for the production of steam or power generates a residue broadly known as ash. All but a few fuels have solid residues, and in some instances, the quantity is considerable (see Table I).
For continuous operation, removal of ash is essential. In suspension firing the ash particles are carried out of the boiler furnace by the gas stream and form deposits on the tubes in the gas passes (fouling). Under some circumstances, the deposits may lead to corrosion of these surfaces.
Some means must be provided to remove the ash from the boiler surfaces since ash in its various forms may seriously interfere with operation or even cause shutdown. Furnace wall and convection-pass surfaces can be cleaned of ash and slag while in operation by the use of sootblowers using steam or air as a blowing medium. The sootblowing equipment directs product air through retractable nozzles aimed at the areas where deposits accumulate.
The convective pass surfaces in the boiler, sometimes referred to as heat traps, are divided into distinct sections in the boiler. Each heat trap normally has its own dedicated set of sootblowing equipment. Usually, only one set of sootblowers is operated at any time, since the sootblowing operation consumes product steam and at the same time reduces the heat transfer rate of the heat trap being cleaned.
TABLE I ______________________________________ Commercial Fuels for Steam Production Fuels Containing Little Fuels Containing Ash or No Ash ______________________________________ All coals Natural gas Fuel Oil - "Bunker C" Manufactured gas Refinery Sludge Code-oven gas (clean) Tank residues Refinery gas Refinery coke Distillates Most tars Wood and wood products Other vegetable products Waste-heat gases (most) Blast-Furnace gas Cement-kiln gas Black Liquor ______________________________________
The sequencing and scheduling of the sootblowing operation can be automated by using controls. See U.S. Pat. No. 4,085,438 to Butler, Apr. 18, 1978, for example.
A common practice for sootblowing scheduling is one utilizing fixed time sequences for the boiler cleaning equipment. The timing sequence is established based on plant measurements during startup. This approach does not allow for the on-line adaptation of the sootblowing sequences. Therefore, changes in boiler operation and unit characteristics are not accounted for in this method.
Sootblowing is also commonly done via "operator inspection", which is usually incomplete and leads to over-cleaning and waste of sootblowing steam.
One of the approaches to sootblowing optimization is the calculation of heat transfer coefficients utilizing a mathematical model of the unit and process measurements to determine sootblowing sequences.
A boiler diagnostic package which can be used for sootblowing optimization has been proposed by T. C. Heil et al in an article entitled "Boiler Heat Transfer Model for Operator Diagnostic Information" given at the ASME/IEEE Power Gen. Conference in Oct. 1981 at St. Louis, Mo. The method depends upon estimates of gas side temperatures from coupled energy balances, and the implementation requires extensive recursive computations to solve a series of heat trap equations. This method is used to estimate heat transfer fouling factors. These intermediate results are then used as input to a boiler performance model based on steady state design conditions to estimate cost savings resulting from sootblower initiation. There is no economic optimization, however, and the method does not account for dynamic changes in incremental steam cost. Also the calculations required to accurately model the unit are quite complex and require complicated recursive techniques to solve the equations. Steadystate design conditions (warranty data) are also required to estimate fouling factors of the individual heat traps.
This scheme quantifies the "operator inspection" method. Numerical values indicate the actual levels of fouling and potential savings from cleaning, but this data is not balanced against cost of cleaning and the rate of performance degradation to predict optimal cleaning times.
In considering the above-mentioned approaches to scheduling of boiler cleaning equipment, the following are desired points of a new optimization scheme:
On-line adaptation of sootblowing scheduling; PA1 Use of simple computational algorithm so that a computer is not required; PA1 No requirement for warranty test data; PA1 Incorporation of economic consideration; PA1 Accounting for interactions between various boiler sections; PA1 Allowing for variable definition of heat traps; PA1 Use of available process measurements; PA1 Accounting for variations in cycle times with variations in system parameters such as load; and PA1 Insensitivity to ambient conditions such as fuel analysis and atmospheric temperature.